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The Analysis of Cluster-Randomized Test-Negative Designs: Eliminating Dengue

Abstract

According to the World Health Organization, dengue is the most critical and most rapidly spreading mosquito-borne viral disease in the world and is responsible for the infection of an estimated 380 million people across the globe annually. There is no cure for dengue, making

prevention key to disrupting the rapid progression of this disease into the world's population.

Recent scientific advances target the mosquito's ability to carry and transmit viral diseases. The method motivating this research injects a safe, naturally occurring bacterium called Wolbachia into the mosquito population responsible for the spread of dengue and other arboviruses including Zika, chikungunya, and yellow fever. When successfully introduced into the mosquito population, Wolbachia prevents these viruses from replicating, which reduces the potential of transmission to humans.

This dissertation addresses the statistical evaluation of the impact of studies of such mosquito-based interventions. Collecting reliable evidence for mosquito-borne interventions is often expensive and logistically prohibitive. The Cluster Randomized Test-Negative Design

discussed in this thesis addresses many of the barriers to such vital research. In this trial setting and several variations, I propose and evaluate estimators of intervention impact. These results can be used to better inform policies and protect vulnerable populations.

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